Examining the typical hemodynamic performance of nearly 3000 modern surgical aortic bioprostheses
Bibliographic record
Abstract
OBJECTIVES: The objective of this analysis was to assess the normal haemodynamic performance of contemporary surgical aortic valves at 1 year postimplant in patients undergoing surgical aortic valve replacement for significant valvular dysfunction. By pooling data from 4 multicentre studies, this study will contribute to a better understanding of the effectiveness of surgical aortic valve replacement procedures, aiding clinicians and researchers in making informed decisions regarding valve selection and patient management. METHODS: Echocardiograms were assessed by a single core laboratory. Effective orifice area, dimensionless velocity index, mean aortic gradient, peak aortic velocity and stroke volume were evaluated. RESULTS: The cohort included 2958 patients. Baseline age in the studies ranged from 70.1 ± 9.0 to 83.3 ± 6.4 years, and Society of Thoracic Surgeons risk of mortality was 1.9 ± 0.7 to 7.5 ± 3.4%. Twenty patients who had received a valve model implanted in fewer than 10 cases were excluded. Ten valve models (all tissue valves; n = 2938 patients) were analysed. At 1 year, population mean effective orifice area ranged from 1.46 ± 0.34 to 2.12 ± 0.59 cm2, and dimensionless velocity index, from 0.39 ± 0.07 to 0.56 ± 0.15. The mean gradient ranged from 8.6 ± 3.4 to 16.1 ± 6.2 mmHg with peak aortic velocity of 1.96 ± 0.39 to 2.65 ± 0.47 m/s. Stroke volume was 75.3 ± 19.6 to 89.8 ± 24.3 ml. CONCLUSIONS: This pooled cohort is the largest to date of contemporary surgical aortic valves with echocardiograms analysed by a single core lab. Overall haemodynamic performance at 1 year ranged from good to excellent. These data can serve as a benchmark for other studies and may be useful to evaluate the performance of bioprosthetic surgical valves over time. CLINICAL TRIAL REGISTRATION NUMBER: NCT02088554, NCT02701283, NCT01586910 and NCT01531374.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".